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Classification day 2

Authored by Patrycja Sawicka

Mathematics, Science

1st - 5th Grade

Used 2+ times

Classification day 2
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10 questions

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1.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

What do you mean by generalization in terms of the SVM?

How far the hyperplane is from the support vectors

How accurately the SVM can predict outcomes for unseen data

The threshold amount of error in an SVM

2.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

In SVM, when the C parameter is rising:

Margin will be smaller

Margin will be bigger

C parameter not affects margin

3.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

The effectiveness of an SVM depends upon:

Selection of Kernel

Kernel Parameters

Soft Margin Parameter C

All

4.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

Support vectors are the data points that lie closest to the decision surface.

TRUE

FALSE

5.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

What would happen when you use very small C (C~0)?

Misclassification would happen

Data will be correctly classified

Can’t say

None of these

6.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

If I am using all features of my dataset and I achieve 100% accuracy on my training set, but ~70% on validation set, what should I look out for?

Underfitting

Nothing, the model is perfect

Overfitting

7.

MULTIPLE CHOICE QUESTION

2 mins • 1 pt

In simple linear regression, if you change the input value by 1 then output value will be changed by:

The slope parameter

The intercept parameter

None

1

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